AI processors will lead the era of the Fourth Industrial Revolution
Artificial intelligence (AI) is one of the key emerging technologies. Global IT companies are competitively launching the newest technologies and competition is heating up more than ever. However, most AI technologies focus on software and their operating speeds are low, making them a poor fit for mobile devices. Therefore, many big companies are investing to develop semiconductor chips for running AI programs with low power requirements but at high speeds.
A research team led by Professor Hoi-Jun Yoo of the Department of Electrical Engineering has developed a semiconductor chip, CNNP (CNN Processor), that runs AI algorithms with ultra-low power, and K-Eye, a face recognition system using CNNP. The system was made in collaboration with a start-up company, UX Factory Co.
The K-Eye series consists of two types: a wearable type and a dongle type. The wearable type device can be used with a smartphone via Bluetooth, and it can operate for more than 24 hours with its internal battery. Users hanging K-Eye around their necks can conveniently check information about people by using their smartphone or smart watch, which connects K-Eye and allows users to access a database via their smart devices. A smartphone with K-EyeQ, the dongle type device, can recognize and share information about users at any time.
When recognizing that an authorized user is looking at its screen, the smartphone automatically turns on without a passcode, fingerprint, or iris authentication. Since it can distinguish whether an input face is coming from a saved photograph versus a real person, the smartphone cannot be tricked by the user’s photograph.
The K-Eye series carries other distinct features. It can detect a face at first and then recognize it, and it is possible to maintain “Always-on” status with low power consumption of less than 1mW. To accomplish this, the research team proposed two key technologies: an image sensor with “Always-on” face detection and the CNNP face recognition chip.
The first key technology, the “Always-on” image sensor, can determine if there is a face in its camera range. Then, it can capture frames and set the device to operate only when a face exists, reducing the standby power significantly. The face detection sensor combines analog and digital processing to reduce power consumption. With this approach, the analog processor, combined with the CMOS Image Sensor array, distinguishes the background area from the area likely to include a face, and the digital processor then detects the face only in the selected area. Hence, it becomes effective in terms of frame capture, face detection processing, and memory usage.
The second key technology, CNNP, achieved incredibly low power consumption by optimizing a convolutional neural network (CNN) in the areas of circuitry, architecture, and algorithms. First, the on-chip memory integrated in CNNP is specially designed to enable data to be read in a vertical direction as well as in a horizontal direction. Second, it has immense computational power with 1024 multipliers and accumulators operating in parallel and is capable of directly transferring the temporal results to each other without accessing to the external memory or on-chip communication network. Third, convolution calculations with a two-dimensional filter in the CNN algorithm are approximated into two sequential calculations of one-dimensional filters to achieve higher speeds and lower power consumption.
With these new technologies, CNNP achieved 97% high accuracy but consumed only 1/5000 power of the GPU. Face recognition can be performed with only 0.62mW of power consumption, and the chip can show higher performance than the GPU by using more power.
These chips were developed by Kyeongryeol Bong, a Ph. D. student under Professor Yoo and presented at the International Solid-State Circuit Conference (ISSCC) held in San Francisco in February. CNNP, which has the lowest reported power consumption in the world, has achieved a great deal of attention and has led to the development of the present K-Eye series for face recognition.
Professor Yoo said “AI – processors will lead the era of the Fourth Industrial Revolution. With the development of this AI chip, we expect Korea to take the lead in global AI technology.”
The Latest on: AI processor
- AI chip startup Graphcore closes $200M Series D, adds BMW and Microsoft as strategic investors on December 18, 2018 at 3:08 am
PCIe processor cards to accelerate the deployment of a range of AI-based technologies that intersect with their own R&D labs. Commenting in a statement, Tobias Jahn, principal at BMW i Ventures ... […]
- Graphcore Raises $200M in Series D Funding on December 18, 2018 at 2:10 am
Led by Nigel Toon, CEO and co-founder, Graphcore has built a completely new kind of processor and software for AI and machine intelligence. It has been shipping first products to early access customer... […]
- Graphcore Secures Lead in Global AI Chip Race With $200 Million in New Capital From BMW, Microsoft and Leading Financial Investors on December 17, 2018 at 11:06 pm
Graphcore has built a completely new kind of processor and software for AI and machine intelligence. It has been shipping first products to early access customers and generated first revenues this ... […]
- Wearable AI market worth $42.4 billion by 2023 scrutinized in new research on December 17, 2018 at 6:03 pm
Cloud-Based AI), Component (Processor, Connectivity IC, Sensors), Application (Consumer Electronics, Enterprise, Healthcare), and Geography - Global Forecast to 2023", is projected to reach USD 42.4 b... […]
- Video: How DDN Powers HPC & Ai Applications on December 17, 2018 at 12:54 pm
and solutions fully integrated and optimized for AI and deep learning (DL) workloads: DDN SFA18K—the world’s fastest and most scalable hybrid storage solution that accelerates processors, embeds file ... […]
- Ambarella and HELLA Aglaia Partner to Enable Advanced AI Features in Front ADAS Cameras on December 17, 2018 at 5:25 am
which offers a powerful Image Signal Processor (ISP) and massive Artificial Intelligence (AI) computing performance with extremely low power consumption, typically below 2.5 watts. Combined with ... […]
- $40+ Billion Wearable AI (Smart Watch, Ear Wear, Eye Wear) Market - Global Forecast to 2023 - ResearchAndMarkets.com on December 17, 2018 at 4:45 am
The "Wearable AI Market by Product (Smart Watch, Ear Wear, Eye Wear), Operation (On-Device, Cloud-Based), Component (Processor, Connectivity IC, Sensors), Application (Consumer Electronics, Enterprise ... […]
- MediaTek’s Helio P90 Octa-core processor brings premium AI features to the mid-range on December 14, 2018 at 10:00 am
When you look back at the flagship smartphones that launched during 2018, you’ll find that Qualcomm’s Snapdragon 845 processor powered a big chunk of them, with a healthy smattering of Samsung’s Exyno... […]
- The “Flagship killer” UMIDIGI F1 has an incredible battery life with AI thanks to Android 9.0 Pie on December 14, 2018 at 8:34 am
It is powered by a MediaTek Helio P60(64 bit) Octa-Core AI processor coupled with 4GB of LPDDR4X RAM and a Mali-G72 GPU for graphics-intensive tasks. The F1 also comes with 128GB of internal storage w... […]
- Snapdragon 855 Will Power Android Phones in 2019 With Blazing 5G And AI on December 13, 2018 at 2:05 pm
The Snapdragon 855 features the newest 4 th generation of Qualcomm’s AI Engine, which incorporates the CPU, GPU, Hexagon and all types of cores inside of the Hexagon. This includes support for runtime ... […]
via Google News and Bing News